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Title: Artificial intelligence and deep learning in ophthalmology
Authors: Ting, Daniel Shu Wei
Pasquale, Louis R.
Peng, Lily
Campbell, John Peter
Lee, Aaron Y.
Raman, Rajiv
Tan, Gavin Siew Wei
Schmetterer, Leopold
Keane, Pearse A.
Wong, Tien Yin
Keywords: Science::Medicine
Issue Date: 2018
Source: Ting, D. S. W., Pasquale, L. R., Peng, L., Campbell, J. P., Lee, A. Y., Raman, R., . . . Wong, T. Y. (2018). Artificial intelligence and deep learning in ophthalmology. British Journal of Ophthalmology, 103(2), 167–175. doi:10.1136/bjophthalmol-2018-313173
Project: NHIC-I2D-1409022
STaR/2013; CG/SERI/2010
Journal: The British journal of ophthalmology
Abstract: Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to impact on healthcare. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography and visual fields, achieving robust classification performance in the detection of diabetic retinopathy and retinopathy of prematurity, the glaucoma-like disc, macular oedema and age-related macular degeneration. DL in ocular imaging may be used in conjunction with telemedicine as a possible solution to screen, diagnose and monitor major eye diseases for patients in primary care and community settings. Nonetheless, there are also potential challenges with DL application in ophthalmology, including clinical and technical challenges, explainability of the algorithm results, medicolegal issues, and physician and patient acceptance of the AI 'black-box' algorithms. DL could potentially revolutionise how ophthalmology is practised in the future. This review provides a summary of the state-of-the-art DL systems described for ophthalmic applications, potential challenges in clinical deployment and the path forward.
ISSN: 0007-1161
DOI: 10.1136/bjophthalmol-2018-313173
Schools: Lee Kong Chian School of Medicine (LKCMedicine) 
Rights: © 2019 Author(s) (or their employer(s)). Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

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